Sunday 18th of February 2018

An Improved Particle Swarm Optimization Algorithm and Its Application

Xuesong Yan

In this paper, aim at the disadvantages of standard Particle Swarm Optimization algorithm like being trapped easily into a local optimum, we improves the standard PSO and proposes a new algorithm to solve the overcomes of the standard PSO. The new algorithm keeps not only the fast convergence speed characteristic of PSO, but effectively improves the capability of global searching as well. Compared with standard PSO on the Benchmarks function, the results show that the new algorithm is efficient, we also use the new algorithm to solve the TSP and the experiment results show the new algorithm is effective for the this problem.

Keywords: Particle Swarm Optimization, Traveling Salesman Problem, Particle, Convergence

Download Full-Text


Xuesong Yan
School of Computer Science, China University of Geosciences Wuhan, Hubei 430074, China

IJCSI Published Papers Indexed By:





IJCSI is a refereed open access international journal for scientific papers dealing in all areas of computer science research...

Learn more »
Join Us

Read the most frequently asked questions about IJCSI.

Frequently Asked Questions (FAQs) »
Get in touch

Phone: +230 911 5482

More contact details »